towards a fair (my)data economy · open formats via secure, standardized apis 2. usable data shared...
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Towards a Fair
(My)DataEconomy
Alexandros Nousias, MyData Greece
Deployment PeriodInstallation Period
Maturity
Synergy
Frenzy
Irruption
The techno-economic paradigm (TEP)
Time
Previous Great Surge
source: Carlota Perez: The techno-economic paradigm shift
Degreeof diffusion
of thetechnological
revolution
TEP is a recurring pattern of cyclical movement: from an initial installation period, through a collapse and recession which signify the turning point, to a full deployment period.
Next Great Surge
Turning Point
Health data analysisDo we need it?
81% of NHS + private healthcare sector support
the analysis of anonymized data
Should we analyze?
81%
87% support NHS should receive a fair share of
gains following medical discoveries
Should benefit NHS?
87%
87% support taxpayers should also benefit from gains resulting from any
analysis
Should benefit taxpayer?
87%
Health data analysisWho should do it, and for whom?
Multinationals?12% would be
comfortable with a multinational
carrying out the analysis
Confidentiality?17% believe that
the data will be processed in a
confidential manner
73%
36%
73% of doctors/nurses would recommend their patients use data driven technology
Recommend to patients?
36% said their patients made use of existing health care digital services
Existing patient use?
API ecosystemIn the current structureless API economy, if the number of services grow,then the number of connections between them grow at a faster rate
Government Researchers
Bank
App developers
Grocery/Retail store
Relatives
Mobility service
Electricity company
Healthcare
Web media
Peer groups
Insurance Employers
No infrastructure
Aggregator ModelAggregating data control is easier, but different aggregators do not have a built-inincentive to develop interoperability between them
Government
Researchers
Bank
Relatives
Grocery/Retail store
App developers Mobility
service
Electricity companyHealthcare
Web media
Peer groups
Insurance
Employers
Exclusion
Exclusion is the usual game humans play
Human exclusionToday it feels like 99%
of humans are excluded from their own data
Data exclusion
Exclusion ---> InclusionExclusion is not inherent. It’s a human invention
Data exclusion creates a form of apathy against forces that seem too big to control
Trust is brokenTo rebuild trust we need
to put humans in control of
the data about them
Trust must be rebuilt
Privacy vs. InnovationBuilding dynamically in one another
the right to be free from secret surveillance and to determine whether, when, how, and to whom, one's personal or organizational information is to be revealed
PrivacyThe process of
translating an idea or invention into
a good or service that creates value or for
which customers will pay
Innovation
Trust by DesignMyData. A Nordic Model for human-centered personal data management and processing
Individuals are empowered actors, not passive targets, in the management of their personal lives
1. Human centric control and privacy
It is essential that personal data is technically easy to access and use – it is accessible in machine readable openformats via secure, standardized APIs
2. Usable data
Shared MyData infrastructure enables decentralized management of personal data, improves interoperability, makes it easier for companies to comply with tightening data protection regulations, and allows individuals to change service providers without proprietary data lock-ins
3. Open business environment
MyData ModelCompared to the aggregation model, MyData is resilient systembecause it is not dependent on a single organization or technical infrastructure
Government
Researchers
Bank
Relatives
Grocery/Retail store
App developers
Mobility service
Electricity company
Healthcare
Web media
Peer groups
Insurance
Employers
MyData RolesMyData Account Model
A data source collects and processes personal data which the other roles
(including Persons) may wish to access and use
Data sourceA data using service can be authorized to fetch and use personal data from one or more data sources
Data using service
A Personal Data Operator enables individuals to securely access, manage and use their personal data, as well as to control the flow of personal data with, and between, data sources and data using services
MyData Operator
An individual that manages the use of their own personal data, for their own purposes, and maintains relationships with other individuals, services or organizations
PersonThe architecture: Interoperable &standardized MyData accounts.
For individuals: The account model provides individuals with an easy way to control their personal data from one place even while the data is created, stored, and processed by hundreds of different services.
For developers: The account model facilitates access to data and removes dependencies on specific data aggregators.
MyData accounts will generally be provided by organizations that act as MyData operators. An individual or organization may fulfill one or more roles in the architecture.
Data Flow
Consent Flow
MyData Example (health)MyData and Occupational health
Source A:Purchase
Data
OccupationalHealthProvider
MyData Operator
Data Flow
Consent Flow
Source B:Public Health Care
Data
Organization(employer)
Money Flow
Clinical data usually consist of various test results and diagnosis. Occupational health care providers change when individuals change jobs. There is no convenient way to organize data logistics between different occupation health care providers. Furthermore, getting more data about individuals would significantly help personalize and optimize health and wellbeing services and provide alternative means for diagnosis. The MyData infrastructure can provide standardized methods for managing data logistics between different professional and public health organizations and sources of behavioral data in robust ways across organizations.
MyData shiftsWhat needs to change
Formal RightsIn many countries, individuals have enjoyed legal data protection for decades, yet their rights have remained mostly formal: little known, hard to enforce, and often obscured by corporate practices.
Actionable RightsWe want true transparency and truly informed consent to become the new normal for when people and organizations interact . We intend access and redress, portability, and the right to be forgotten, to become “one-click rights”: rights that are as simple and efficient to use as today’s and tomorrow’s best online services.
Data ProtectionData protection regulation and corporate ethics codes are designed to protect people from abuse and misuse of their personal data by organizations.
Data EmpowermentWe intend to change common practices towards a situation where individuals are both protected and empowered to use the data that organizations hold about them. Examples of such uses include simplifyingadministrative paperwork, processing data from multiple sources to improve one’s self-knowledge, personalized AI assistants, decision-making, and data sharing under the individual’s own terms
Closed EcosystemsToday’s data economy creates network effects favoring a few platforms able to collect and process the largest masses of personal data. These platforms are locking up markets, not just for their competitors, but also for most businesses who risk losing direct access to their customers.
Open EcosystemsBy letting individuals control what happens to their data, we intend to create a truly free flow of data – freely decided by individuals, free from global choke points - and to create balance, fairness, diversity and competition in the digital economy.
A glance to the future of designMyData. A Nordic Model for human-centered personal data management and processing
Less use ofpersonal data
Old paper times
Weak Data Protection
Lot’s of datausage
Strong Data Protection
Complying with regulation
Organizations decide
how data is used
People decidehow data is used
Positioning: Amara's lawWe tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run
Visibility
Time
Peak of Inflated Expectations
Technology Trigger
Trough of Disillusionment
Slope of Enlightenment
Plateau of Productivity
MyData in Amara’s LawIt takes a lot of time to apply knowledge in a productive way, beyond the initial hype
Visibility
Time
Applied Knowledge
Hype
Deployment PeriodInstallation Period
Maturity
Synergy
Frenzy
Irruption
Turning PointPeak of Inflated Expectations
Technology Trigger
Trough of Disillusionment
Slope of Enlightenment
Plateau of Productivity
TEP and Amara’s law
Time
Degreeof diffusion
of thetechnological
revolution
The recurring pattern of cyclical movement described by TEP and Amara's law, describing how we overestimate the effect of a technology in the short run and underestimate the effect in the long run.
Visibility
Big opportunities for business Trust is required!
Final thoughts
From sick care to preventive health care by individual involvement
Data guardians • People• Parties• Operators
Create a “data civilization” to grasp the opportunities and transcend society/individual disciplines
Digital Health Ecosystemopen – ethical – trustworthy
IPR
Privacy
GDPR
Public Interest
Innovation
Market
Ethics
Thank YouAlexandros Nousias
Alexandros NousiasNCSR-DemokritosMyData GreeceGFOSS
@alexnousias
https://www.linkedin.com/in/alexandrosnoussias/
alexandros.nousias@gmail.com
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